Code and documentation for the collaboration with PrathamBooks during Sprint' 2018
At the time of committing this readme file, Pratham Books' StoryWeaver platform has 8000+ books in 113 languages (70+ International languages and 30+ Indian Languages) distributed across 25+ categories with hundred of tags. As StoryWeaver scales up to host 20K stories over next year or so, discoverability of books (inside the StoryWeaver platform as well as across the web via search engines) could be a challenge. DataKind intends to solve this using various Natural Language Processing and Machine Learning tools out there.
Build a tool to generate relevant tags for each story to improve the searchability of content on StoryWeaver platform.
Most Important rule of collaborating Ask Questions. We encourage all kinds of questions. As a community we respect your will to contribute and we want to help you do that. So, reach us out over slack or raise an issue on github with your question.
Incase you are not on our slack follow the link to join us and join the channel #pratham_books (How to join a channel) and incase you are new to Github checkout how to create an Issue here.
Contributions are expected in the form of pull requests (How to create a PR?). All your work must be donated under MIT License, too.
File Name: stories_pages.csv
stories_pages.csv is the main table. It captures most of the attributes of the story including title, synopsis, content, language, reading level etc.
story_id - Unique Numeric identifier for a story
story_title - Title of the story
story_english_title - Title of the English version of the story
is_child_created_story - If the story created by a child
stories_status - If the story is published or not. A story may be in the draft status etc. In that case, it will not be published.
stories_summary - Synopsis of the story
ancestry - Parent child relationship between different versions of the same story
is_recommended_story - If the story is displayed as recommended on the StroyWeaver platform
reads - Total Number of reads for the story
language_name - Language of the story
organization_name - If the story is from a Publisher, name of the Publisher/Organization.
page_id - A Story consists of multiple pages. Numeric identifier of each page.
page_content - Content of the page (if any).
page_type - Type of the page
story_derivation_type - If it's a original story or a derived (Translated or Releveled) one
story_publishing_type - If it's from a Publisher or from a Community User
reading_level_cat - Reading Level of the Story (1 - 4)File Name : stories_categories.csv
stories_categories.csv table captures categories associated with each story
story_id - Unique Numeric identifier for a story
story_title - Title of the story
story_english_title - Title of the English version of the story
category_name - Name of the category associated with the storyFile Name : stories_tags.csv
stories_tags table captures tags associated with each story
story_id - Unique Numeric identifier for a story
story_title - Title of the story
story_english_title - Title of the English version of the story
story_tag_name - Name of the tag associated with the story|
|- data
| |- raw <- Original datadump supplied by Partner Organization
| |- external <- External data (if any)
| |- processed <- Final data after cleaning etc
|
|- r <- All code composed using R programming language live here
| |- src <- Scripts for visualization, modeling etc
| |- notebooks <- RMarkdown Notebooks
| |- reports <- Generated analysis as HTML, PDF
|
|
|- python <- All code composed using python programming language live here
| |- src <- Source code for visualization, modeling etc
| |- notebooks <- Jupyter Notebooks
| |- reports. <- Generated analysis as HTML, PDF
| |- requirements.txt <- The requirements file for reproducing the python analysis environment
|
|- readme.txt <- Readme file (YOU ARE HERE!)